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Multifractal cross-correlation spectra analysis on Chinese stock markets

Author

Listed:
  • Zhao, Xiaojun
  • Shang, Pengjian
  • Shi, Wenbin

Abstract

In this paper, the long-range cross-correlation of Chinese stock indices is systematically studied. The multifractal detrended cross-correlation analysis (MF-DXA) appears to be one of the most effective methods in detecting long-range cross-correlation of two non-stationary variables. The Legendre spectrum and the large deviations spectrum are extended to the cross-correlation case, so as to present multifractal structure of stock return and volatility series. It is characterized of the multifractality in Chinese stock markets, partly due to clusters of local detrended covariance with large and small magnitudes.

Suggested Citation

  • Zhao, Xiaojun & Shang, Pengjian & Shi, Wenbin, 2014. "Multifractal cross-correlation spectra analysis on Chinese stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 402(C), pages 84-92.
    • Handle: RePEc:eee:phsmap:v:402:y:2014:i:c:p:84-92
    DOI: 10.1016/j.physa.2014.01.066
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    Citations

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    Cited by:

    1. Dong, Keqiang & Zhang, Hong & Gao, You, 2017. "Dynamical mechanism in aero-engine gas path system using minimum spanning tree and detrended cross-correlation analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 465(C), pages 363-369.
    2. Day, Min-Yuh & Ni, Yensen & Huang, Paoyu, 2019. "Trading as sharp movements in oil prices and technical trading signals emitted with big data concerns," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 349-372.
    3. He, Qian & Huang, Jingjing, 2020. "A method for analyzing correlation between multiscale and multivariate systems—Multiscale multidimensional cross recurrence quantification (MMDCRQA)," Chaos, Solitons & Fractals, Elsevier, vol. 139(C).
    4. Dai, Meifeng & Hou, Jie & Gao, Jianyu & Su, Weiyi & Xi, Lifeng & Ye, Dandan, 2016. "Mixed multifractal analysis of China and US stock index series," Chaos, Solitons & Fractals, Elsevier, vol. 87(C), pages 268-275.
    5. Ni, Yensen & Cheng, Yirung & Huang, Paoyu & Day, Min-Yuh, 2018. "Trading strategies in terms of continuous rising (falling) prices or continuous bullish (bearish) candlesticks emitted," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 501(C), pages 188-204.
    6. Ladislav Kristoufek, 2016. "Power-law cross-correlations estimation under heavy tails," Papers 1602.05385, arXiv.org, revised Apr 2016.
    7. Xi, Caiping & Zhang, Shuning & Xiong, Gang & Zhao, Huichang & Yang, Yonghong, 2017. "The application of the multifractal cross-correlation analysis methods in radar target detection within sea clutter," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 468(C), pages 839-854.
    8. Gu, Danlei & Huang, Jingjing, 2019. "Multifractal detrended fluctuation analysis on high-frequency SZSE in Chinese stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 521(C), pages 225-235.
    9. Yang, Liansheng & Zhu, Yingming & Wang, Yudong & Wang, Yiqi, 2016. "Multifractal detrended cross-correlations between crude oil market and Chinese ten sector stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 462(C), pages 255-265.

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